Ruslan Salakhutdinov, Apple AI leader, thoughts on deep learning:
https://www.technologyreview.com/s/603912/apples-ai-director-heres-how-to-supercharge-deep-learning/
#apple #deeplearning #theory
https://www.technologyreview.com/s/603912/apples-ai-director-heres-how-to-supercharge-deep-learning/
#apple #deeplearning #theory
MIT Technology Review
Apple’s AI Director: Here’s How to Supercharge Deep Learning
Apple’s director of artificial intelligence, Ruslan Salakhutdinov, believes that the deep neural networks that have produced spectacular results in recent years could be supercharged in coming years by the addition of memory, attention, and general knowledge.…
Recent Advances for a Better Understanding of Deep Learning − Part I
https://towardsdatascience.com/recent-advances-for-a-better-understanding-of-deep-learning-part-i-5ce34d1cc914
#dl #theory
https://towardsdatascience.com/recent-advances-for-a-better-understanding-of-deep-learning-part-i-5ce34d1cc914
#dl #theory
Medium
Recent Advances for a Better Understanding of Deep Learning
I would like to live in a world whose systems are build on rigorous, reliable, verifiable knowledge, and not on alchemy. […] Simple…
What is a Generative Adversarial Network?
Another article about how GANs work.
http://hunterheidenreich.com/blog/what-is-a-gan/
#gan #theory #dl
Another article about how GANs work.
http://hunterheidenreich.com/blog/what-is-a-gan/
#gan #theory #dl
Hunter Heidenreich
What is a Generative Adversarial Network?
Looking into what a generative adversarial network is to understand how they work.
Alan Turing will become a face of new £50 note
That's a great acknowledgment of the man who stands behind most of the theoretical computing.
Link: https://www.bbc.com/news/business-48962557
Most famous Turing's work 'On computable numbers': https://www.cs.virginia.edu/~robins/Turing_Paper_1936.pdf
Turing machine: https://en.wikipedia.org/wiki/Turing_machine
#Turing #Theory #Math #history
That's a great acknowledgment of the man who stands behind most of the theoretical computing.
Link: https://www.bbc.com/news/business-48962557
Most famous Turing's work 'On computable numbers': https://www.cs.virginia.edu/~robins/Turing_Paper_1936.pdf
Turing machine: https://en.wikipedia.org/wiki/Turing_machine
#Turing #Theory #Math #history
The HSIC Bottleneck: Deep Learning without Back-Propagation
An alternative to conventional backpropagation, that has a number of distinct advantages.
Link: https://arxiv.org/abs/1908.01580
#nn #backpropagation #DL #theory
An alternative to conventional backpropagation, that has a number of distinct advantages.
Link: https://arxiv.org/abs/1908.01580
#nn #backpropagation #DL #theory
arXiv.org
The HSIC Bottleneck: Deep Learning without Back-Propagation
We introduce the HSIC (Hilbert-Schmidt independence criterion) bottleneck for training deep neural networks. The HSIC bottleneck is an alternative to the conventional cross-entropy loss and...
Matus Telgarsky’s Deep Learning Theory course
Course syllabus, lecture handout materials from Illinois university.
Link: http://mjt.cs.illinois.edu/courses/dlt-f19/
#MOOC #DL #Theory #Course
Course syllabus, lecture handout materials from Illinois university.
Link: http://mjt.cs.illinois.edu/courses/dlt-f19/
#MOOC #DL #Theory #Course